UCSF partners with Oura smart ring to study early detection of COVID-19

man sleeping in bed wearing Oura smart ring to track vital signs
UCSF researchers plan to use data from the Oura smart ring to build an algorithm to help identify patterns of onset, progression, and recovery, for COVID-19. (Oura)

The University of California San Francisco is arming 2,000 frontline healthcare workers with the Oura smart ring for potential early detection of COVID-19 symptoms.

The Finnish startup, which has U.S. headquarters in San Francisco, is sponsoring research at UCSF to study whether physiological data collected by the Oura ring, combined with responses to daily symptom surveys, can predict illness symptoms.

The study aims to build an algorithm to help UCSF identify patterns of onset, progression, and recovery, for COVID-19, the company said.

The UCSF TemPredict study will focus on front-line healthcare workers and will also be open to Oura users in the general population.

Consumer adoption of wearables like the Fitbit and Apple Watch has quickly grown but doctors have questioned the clinical value of the data. Apple added an electrocardiogram feature to the latest version of the Apple Watch but cardiologists have cautioned that the ECG feature is not reliable to detect atrial fibrillation.

Researchers and clinicians now see opportunities to use wearables data for disease tracking and surveillance.

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The study is especially urgent as nationwide frontline healthcare workers are at risk of passing the virus while asymptomatic. Six UCSF healthcare workers are currently diagnosed with the virus, and two ER doctors remain in critical condition from COVID-19 in Washington state and New Jersey.

The smart rings can track changes in users' body temperature, respiratory rate, and heart rate. Healthcare workers using the rings can use this information to better understand early warning signs of infection and to seek treatment, isolate themselves or stay home from work, according to the company.

The research team has hypothesized that the Oura ring could anticipate COVID-19 onset by as many as two to three days before the onset of more obvious symptoms, like coughing.

The research team hopes to develop a COVID-19 early detection device by fall, when infectious disease experts worry coronavirus will return for a second wave, the San Francisco Chronicle reported.

“It will help people self-quarantine sooner, get treatment sooner,” said Dr. Ashley Mason, the UCSF assistant psychiatry professor who developed the project and is the lead investigator, according to the San Francisco Chronicle.

“It’s expected back in the fall and we need to have tools ready, Mason said.

Oura is conducting the research in partnership with the University of California healthcare providers and schools, and doctors at both UCSF and the University of California San Diego are running the study. 

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The Oura smart ring's ability to track body temperature is an important biological signal, according to Ben Smarr, Ph.D., an assistant professor of bioengineering and data science at UCSD, who will help crunch data as part of the study.

Smarr believes continuous data from wearables can be highly valuable in tracking health and predicting illness.

"When you have time-series data, so temperature every minute instead of once a day that turns it from biomarker into a signal. We can begin to reimagine how healthcare works," he said.

He added, "This opportunity came along with UCSF to focus this research where we can make a difference and build some COVID detection systems."

Researchers will use this information as they attempt to identify patterns that could predict onset, progression, and recovery in future cases of COVID-19. If this approach is successful, it could open the door for research into tracking and managing other illnesses and conditions, the research team said.

Scripps using Fitbit, Apple Watch data

Scripps Research Translational Institute has launched an app-based research study to analyze data from smartwatches or activity trackers, such as a Fitbit, Apple Watch, Amazfit or Garmin Watch.

The study, called DETECT, aims to test whether this data—including heart rates, sleep and activity levels—can help to more quickly detect the emergence of influenza, coronavirus and other fast-spreading viral illnesses.

Researchers are seeking members of the public who are 18 or older and use a smartwatch or activity tracker, such as a Fitbit, Apple Watch, Amazfit or Garmin Watch, to join the study and consent to share their data through the MyDataHelps mobile app.

By using key data points from these wearable devices, scientists believe they can improve real-time surveillance of contagious respiratory illnesses.

RELATED: Former FDA chief Gottlieb has dire warnings about hitting the brakes on social distancing measures

Early detection is critical for effective public health response to infectious disease outbreaks and for improving treatments.

"In light of the ongoing flu season and the global pandemic of COVID-19, we see enormous opportunity to enhance disease tracking for improved population health,” says Jennifer Radin, Ph.D., an epidemiologist at the Scripps Research Translational Institute who is leading the study. “One way to do this is to leverage and analyze the rich health data that’s already being collected by the millions of Americans who regularly use wearable devices.”

Scripps Research is working with health technology company CareEvolution on the study.

“Scripps Research’s prior work has demonstrated that passively collected data from consumer-grade wearable technologies can be not only a valuable marker of recent and current flu-like illnesses but a promising predictor of an impending illness that may not be perceived by the individual yet,” said Vik Kheterpal, MD, principal at CareEvolution.

Earlier this year, a study by Scripps Research Translational Institute showed that by analyzing de-identified data from approximately 47,000 users of Fitbit devices equipped with heart rate tracking capabilities, they could significantly improve predictions of influenza-like illness at the state level when compared with data from the CDC. 

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